{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dates and Times\n",
    "\n",
    "A special type of categorical variable are those that instead of taking traditional labels, like color (blue, red), or city (London, Manchester), take dates as values. For example, date of birth ('29-08-1987', '12-01-2012'), or time of application ('2016-Dec', '2013-March').\n",
    "\n",
    "Datetime variables can contain dates only, or time only, or date and time.\n",
    "\n",
    "Typically, we would never work with a date variable as a categorical variable, for a variety of reasons:\n",
    "\n",
    "- Date variables usually contain a huge number of individual categories, which will expand the feature space dramatically\n",
    "- Date variables allow us to capture much more information from the dataset if preprocessed in the right way\n",
    "\n",
    "In addition, often, date variables will contain dates that were not present in the dataset that we used to train the machine learning algorithm. In fact, will contain dates placed in the future respect to the dates present in the dataset we used to train. Therefore, the machine learning model will not know what to do with them, because it never saw them while being trained. \n",
    "\n",
    "**I will cover different was of pre-processing/engineering date variables in the section \"Engineering date variables\".**\n",
    "\n",
    "=============================================================================\n",
    "\n",
    "\n",
    "## Real Life example: Peer to peer lending (Finance)\n",
    "\n",
    "### Lending Club\n",
    "\n",
    "**Lending Club** is a peer-to-peer Lending company based in the US. They match people looking to invest money with people looking to borrow money. When investors invest their money through Lending Club, this money is passed onto borrowers, and when borrowers pay their loans back, the capital plus the interest passes on back to the investors. It is a win for everybody as they can get typically lower loan rates and higher investor returns.\n",
    "\n",
    "If you want to learn more about Lending Club follow this [link](https://www.lendingclub.com/).\n",
    "\n",
    "The Lending Club dataset contains complete loan data for all loans issued through 2007-2015, including the current loan status (Current, Late, Fully Paid, etc.) and latest payment information. Features include credit scores, number of finance inquiries, address including zip codes and state, and collections among others. Collections indicates whether the customer has missed one or more payments and the team is trying to recover their money.\n",
    "\n",
    "The file is a matrix of about 890 thousand observations and 75 variables. More detail on this dataset can be found in [Kaggle's website](https://www.kaggle.com/wendykan/lending-club-loan-data)\n",
    "\n",
    "Let's go ahead and have a look at the variables!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "====================================================================================================\n",
    "\n",
    "To download the Lending Club loan book from Kaggle go to this [website](https://www.kaggle.com/wendykan/lending-club-loan-data)\n",
    "\n",
    "Scroll down to the bottom of the page, and click on the link 'loan.csv', and then click the 'download' blue button towards the right of the screen, to download the dataset.\n",
    "Unzip it, and save it to a directory of your choice.\n",
    "\n",
    "**Note that you need to be logged in to Kaggle in order to download the datasets**.\n",
    "\n",
    "If you save it in the same directory from which you are running this notebook, then you can load it the same way I will load it below.\n",
    "\n",
    "===================================================================================================="
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>loan_amnt</th>\n",
       "      <th>grade</th>\n",
       "      <th>issue_d</th>\n",
       "      <th>purpose</th>\n",
       "      <th>last_pymnt_d</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>B</td>\n",
       "      <td>Dec-2011</td>\n",
       "      <td>credit_card</td>\n",
       "      <td>Jan-2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2500.0</td>\n",
       "      <td>C</td>\n",
       "      <td>Dec-2011</td>\n",
       "      <td>car</td>\n",
       "      <td>Apr-2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2400.0</td>\n",
       "      <td>C</td>\n",
       "      <td>Dec-2011</td>\n",
       "      <td>small_business</td>\n",
       "      <td>Jun-2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10000.0</td>\n",
       "      <td>C</td>\n",
       "      <td>Dec-2011</td>\n",
       "      <td>other</td>\n",
       "      <td>Jan-2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3000.0</td>\n",
       "      <td>B</td>\n",
       "      <td>Dec-2011</td>\n",
       "      <td>other</td>\n",
       "      <td>Jan-2016</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   loan_amnt grade   issue_d         purpose last_pymnt_d\n",
       "0     5000.0     B  Dec-2011     credit_card     Jan-2015\n",
       "1     2500.0     C  Dec-2011             car     Apr-2013\n",
       "2     2400.0     C  Dec-2011  small_business     Jun-2014\n",
       "3    10000.0     C  Dec-2011           other     Jan-2015\n",
       "4     3000.0     B  Dec-2011           other     Jan-2016"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# let's load the Lending Club dataset with a few selected columns\n",
    "\n",
    "use_cols = ['loan_amnt', 'grade', 'purpose', 'issue_d', 'last_pymnt_d']\n",
    "\n",
    "data = pd.read_csv('loan.csv', usecols=use_cols)\n",
    "\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "loan_amnt       float64\n",
       "grade            object\n",
       "issue_d          object\n",
       "purpose          object\n",
       "last_pymnt_d     object\n",
       "dtype: object"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# let's inspect at the pandas type of object used to store the information\n",
    "\n",
    "data.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>issue_d</th>\n",
       "      <th>issue_dt</th>\n",
       "      <th>last_pymnt_d</th>\n",
       "      <th>last_pymnt_dt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Dec-2011</td>\n",
       "      <td>2011-12-01</td>\n",
       "      <td>Jan-2015</td>\n",
       "      <td>2015-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Dec-2011</td>\n",
       "      <td>2011-12-01</td>\n",
       "      <td>Apr-2013</td>\n",
       "      <td>2013-04-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Dec-2011</td>\n",
       "      <td>2011-12-01</td>\n",
       "      <td>Jun-2014</td>\n",
       "      <td>2014-06-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Dec-2011</td>\n",
       "      <td>2011-12-01</td>\n",
       "      <td>Jan-2015</td>\n",
       "      <td>2015-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Dec-2011</td>\n",
       "      <td>2011-12-01</td>\n",
       "      <td>Jan-2016</td>\n",
       "      <td>2016-01-01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    issue_d   issue_dt last_pymnt_d last_pymnt_dt\n",
       "0  Dec-2011 2011-12-01     Jan-2015    2015-01-01\n",
       "1  Dec-2011 2011-12-01     Apr-2013    2013-04-01\n",
       "2  Dec-2011 2011-12-01     Jun-2014    2014-06-01\n",
       "3  Dec-2011 2011-12-01     Jan-2015    2015-01-01\n",
       "4  Dec-2011 2011-12-01     Jan-2016    2016-01-01"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# now let's parse the dates, currently coded as strings, into datetime format\n",
    "# this will allow us to make some analysis afterwards\n",
    "\n",
    "data['issue_dt'] = pd.to_datetime(data.issue_d)\n",
    "data['last_pymnt_dt'] = pd.to_datetime(data.last_pymnt_d)\n",
    "\n",
    "data[['issue_d', 'issue_dt', 'last_pymnt_d', 'last_pymnt_dt']].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1a562c77b8>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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cVc65i5xzF/X399dmsyIiIiIiUneJdKLg+9HZx2v6vJoFRMEEuc8DDznn/vcKt/0H8Ifm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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a546877b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# let's see how much money Lending Club has disbursed\n",
    "# (i.e., lent) over the years to the different risk\n",
    "# markets (grade variable)\n",
    "\n",
    "fig = data.groupby(['issue_dt', 'grade'])['loan_amnt'].sum().unstack().plot(\n",
    "    figsize=(14, 8), linewidth=2)\n",
    "\n",
    "fig.set_title('Disbursed amount in time')\n",
    "fig.set_ylabel('Disbursed Amount (US Dollars)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lending Club seems to have increased the amount of money lent from 2013 onwards. The tendency indicates that they continue to grow. In addition, we can see that their major business comes from lending money to C and B grades.\n",
    "\n",
    "'A' grades are the lower risk borrowers, this is borrowers that most likely will be able to repay their loans, as they are typically in a better financial situation. Borrowers within this grade are typically charged lower interest rates.\n",
    "\n",
    "E, F and G grades represent the riskier borrowers. Usually borrowers in somewhat tighter financial situations, or for whom there is not sufficient financial history to make a reliable credit assessment. They are typically charged higher rates, as the business, and therefore the investors, take a higher risk when lending them money."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "Lending Club lends the biggest fraction to borrowers that intend to use that money to repay other debt or credit cards."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "**That is all for this demonstration. I hope you enjoyed the notebook, and see you in the next one.**"
   ]
  }
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